دانلود مقاله ISI انگلیسی شماره 78833
عنوان فارسی مقاله

یک الگوریتم تکاملی کمک-جانشین بر اساس هدف تنوع ژنتیکی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
78833 2015 14 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A surrogate-assisted evolutionary algorithm based on the genetic diversity objective
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 36, November 2015, Pages 87–100

کلمات کلیدی
مدل های رحم جایگزین؛ Metamodels؛ الگوریتم های ممتیک؛ تنوع ژنتیکی؛ طراحی الگوریتم تکاملی
پیش نمایش مقاله
پیش نمایش مقاله یک الگوریتم تکاملی کمک-جانشین بر اساس هدف تنوع ژنتیکی

چکیده انگلیسی

In this work, a novel surrogate-assisted memetic algorithm is proposed which is based on the preservation of genetic diversity within the population. The aim of the algorithm is to solve multi-objective optimization problems featuring computationally expensive fitness functions in an efficient manner. The main novelty is the use of an evolutionary algorithm as global searcher that treats the genetic diversity as an objective during the evolution and uses it, together with a non-dominated sorting approach, to assign the ranks. This algorithm, coupled with a gradient-based algorithm as local searcher and a back-propagation neural network as global surrogate model, demonstrates to provide a reliable and effective balance between exploration and exploitation. A detailed performance analysis has been conducted on five commonly used multi-objective problems, each one involving distinct features that can make the convergence difficult toward the Pareto-optimal front. In most cases, the proposed algorithm outperformed the other state-of-the-art evolutionary algorithms considered in the comparison, assuring higher repeatability on the final non-dominated set, deeper convergence level and higher convergence rate. It also demonstrates a clear ability to widely cover the Pareto-optimal front with larger percentage of non-dominated solutions if compared to the total number of function evaluations.

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